A Digital Twin Architecture to Optimize Productivity within Controlled Environment Agriculture

Abstract

To ensure food security, agricultural production systems should innovate in the direction of increasing production while reducing utilized resources. Due to the higher level of automation with respect to traditional agricultural systems, Controlled Environment Agriculture (CEA) applications generally achieve better yields and quality crops at the expenses of higher energy consumption. In this context, Digital Twin (DT) may constitute a fundamental tool to reach the optimization of the productivity, intended as the ratio between production and resource consumption. For this reason, a DT Architecture for CEA systems is introduced within this work and applied to a case study for its validation. The proposed architecture is potentially able to optimize productivity since it utilizes simulation software that enables the optimization of: (i) Climate control strategies related to the control of the crop microclimate; (ii) treatments related to crop management. Due to the importance of food security in the worldwide landscape, the authors hope that this work may impulse the investigation of strategies for improving the productivity of CEA systems.

Toward the Next Generation of Digitalization in Agriculture Based on Digital Twin Paradigm

“…Their proposed digital twin system consists of a monitoring system to collect environmental condition data from an underground farm, as well as data analysis and modeling techniques to identify key parameters, critical trends, and forecast operational scenarios. Furthermore, digital twin was able to optimize productivity of crops in a greenhouse environment through climate control strategies and treatments related to crop management [74].…”

“…Vertical farming Environmental conditions assessment, identification of forecasting and decision support models, monitoring and optimization of agri-food lifecycle [36] Plant/tree Plant condition monitoring including structure, health, stress, and quality of fruit [31] Robot Analysis and performance evaluation, robot selection, and navigation [35] Robot Simulation of field environment, autonomous robot navigation [68] Agricultural machinery Development and advantages of business models for potato harvesting [59] Agricultural landscape Resource distribution management over different stakeholders in agriculture [72] Crop Forecasting yield and duration of plant development [33] Agricultural machinery Development of three-dimensional geometric models, drawings of devices, mechanisms, and the attributive data [87] Plant Detection of plant diseases and nutrient efficiency [32] Crop/hydroponic farm Identification of crop growth parameters such as lighting, external temperature, and ventilation systems [73] Crop Optimize productivity, climate control strategies, and crop treatment management in controlled environment agriculture [74] Robot Co-simulation of robot environment, prediction of robot movement, and safety monitoring [67] Table 4. Summary of digital twin for post-harvest process.…”

Digital Twins in the Automotive Industry: The Road toward Physical-Digital Convergence

“…The monitoring of land assets by installing various tools and sensors, i.e., in water, temperature, and humidity, for crop protection, maximization of profits, and reduction of failures [36][37][38][39][40][41].…”

Setting up a Digital Twin Assisted Greenhouse Architecture

“…In this context, Chaux's methodology based on virtual simulation technology is used for indicative development of the DT greenhouse architecture (Chaux et al, 2021;Traoré, 2021). It proposes a strategy to modernize production with DT systems including the following elements depicted in Table 2.…”

“…According to Chaux's methodology, 'The data necessary for the optimization must be available in the cloud and the user must download them in his/her local device. The optimization occurs in the local device and the optimal crop treatment and climate control strategy are communicated to the controller for its implementation through a gateway (Chaux et al, 2021).…”